Evidence map›Paper›PMID 42049443›Full record

ArticleIn vivo (Athens, Greece)

Geometric Transformation Algorithm for Acetabular Cup Orientation: Converting 2D Radiographic Projections to 3D Spatial Positioning.

Gökmen Aktas, Lukas Hensler, Sabine Dippel, Pia Heins, Jorge Mayor, Jan-Dierk Clausen, Emmanouil Liodakis, Stephan Sehmisch, Tarek Omar Pacha

Abstract read
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Article in In vivo (Athens, Greece). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Gökmen Aktas *Department of Trauma Surgery, Hannover Medical School, Hannover, Germany; aktas.goekmen@mh-hannover.de.
Lukas HenslerUniversity of Applied Sciences and Arts, Department of Electrical Engineering and Information Technology, Hannover, Germany.
Sabine DippelUniversity of Applied Sciences and Arts, Department of Electrical Engineering and Information Technology, Hannover, Germany.
Pia HeinsUniversity of Applied Sciences and Arts, Department of Electrical Engineering and Information Technology, Hannover, Germany.
Jorge MayorDepartment of Trauma Surgery, Hannover Medical School, Hannover, Germany.
Jan-Dierk ClausenDepartment of Trauma Surgery, Hannover Medical School, Hannover, Germany.
Emmanouil LiodakisDepartment of Trauma Surgery, Hannover Medical School, Hannover, Germany.
Stephan SehmischDepartment of Trauma Surgery, Hannover Medical School, Hannover, Germany.
Tarek Omar Pacha *Department of Trauma Surgery, Hannover Medical School, Hannover, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

aimHip replacement is one of the most common and successful surgeries of our time. However, with increasing numbers of total hip arthroplasties, postoperative complications due to inadequate cup positioning are rising. Accurate measurement of acetabular cup inclination and anteversion is critical for optimal outcomes. While various measurement systems exist, they often require additional hardware, specialized training, or lack integration across the care continuum. This study aims to develop and validate software for automated measurement of acetabular cup positioning, comparing its performance to standard CAD measurements. MATERIALS AND

methodsThe geometric basis for analyzing the acetabular cup is that a hemisphere in 2D projection forms an ellipse, described by a conic section equation. We developed a Python-based software utilizing computer vision techniques for edge detection and ellipse fitting to determine anteversion and inclination from standard radiographs. The software was trained and validated using X-ray images of a pelvic phantom with a conventional acetabular cup (Allofit, Zimmer Biomet) at various predefined angles. CAD software (MediCAD) served as the validation standard. The intraclass correlation coefficient (ICC) quantified agreement between methods.

resultsA total of 140 AP X-ray images were analyzed. Inclination averaged 50.69°±15.86° with our software versus 49.40°±15.24° with CAD. Anteversion averaged 14.36°±9.08°

conclusionOur computer-assisted measurement technique demonstrates excellent concordance with standard methodologies while offering workflow advantages. These results provide a foundation for implementation within computer vision models for automated spatial positioning recognition. Future development will focus on enhancing automation, validating across diverse populations and implant designs, and comparing with 3D computed tomography (CT) measurements.

Indexed as

AcetabulumAlgorithmsArthroplasty, Replacement, HipImaging, Three-DimensionalHip ProsthesisHumansImage Processing, Computer-AssistedPhantoms, ImagingSoftwareTomography, X-Ray ComputedarthroplastyArtificial intelligencecomputer visionhipsurgerytraumatology

Identifiers

PMID42049443
PMCPMC13133850

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.